© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com Cerebral Cortex, 2020;00: 1–17 doi: 10.1093/cercor/bhaa219 Original Article ORIGINAL ARTICLE Causal Role of the Dorsolateral Prefrontal Cortex in Belief Updating under Uncertainty Stefan Schulreich and Lars Schwabe Department of Cognitive Psychology, Faculty of Psychology and Human Movement Science, Universität Hamburg, 20146 Hamburg, Germany Address correspondence to Stefan Schulreich, Department of Cognitive Psychology, Universität Hamburg, Von-Melle-Park 5, 20146 Hamburg, Germany. Email: stefan.schulreich@uni-hamburg.de Abstract Adaptive performance in uncertain environments depends on the ability to continuously update internal beliefs about environmental states. Recent correlative evidence suggests that a frontoparietal network including the dorsolateral prefrontal cortex (dlPFC) supports belief updating under uncertainty, but whether the dlPFC serves a “causal” role in this process is currently not clear. To elucidate its contribution, we leveraged transcranial direct current stimulation (tDCS) over the right dlPFC, while 91 participants performed an incentivized belief-updating task. Participants also underwent a psychosocial stress or control manipulation to investigate the role of stress, which is known to modulate dlPFC functioning. We observed enhanced monetary value updating after anodal tDCS when it was normatively expected from a Bayesian perspective. A model-based analysis indicates that this effect was driven by belief updating. However, we also observed enhanced non-normative value updating, which might have been driven instead by expectancy violation. Enhanced normative and non-normative value updating reflected increased vs. decreased Bayesian rationality, respectively. Furthermore, cortisol increases were associated with enhanced positive, but not with negative, value updating. The present study thereby sheds light on the causal role of the right dlPFC in the remarkable human ability to navigate uncertain environments by continuously updating prior knowledge following new evidence. Key words: belief updating, decision-making, DLPFC, tDCS, uncertainty Introduction Making optimal decisions in the face of uncertain or incomplete information poses a common problem in everyday life. Imagine traveling to another country in an unfamiliar climate zone. Before leaving your hotel on the first day, you are uncertain if it would rain or not and whether it is therefore wise to take an umbrella with you. After 5 days of intermittent heavy rain, you likely think it is wise to do so. Adaptive decision-making in such an environment critically depends on learning from outcomes to reduce uncertainty about environmental states. Now compare this to the decision whether to gamble on the toss of a fair coin with known probabilities of 50% for each possible—but still uncertain—outcome. If you observe 5 “heads”in a row, this may be surprising, but adaptive decision-making requires here to disregard these outcomes since they do not provide any new information on the a priori known probabilities. These examples demonstrate that optimal decision-making requires taking into account the nature of uncertainty. Leav- ing aside differences in autocorrelation (which is typically given for weather but not for random coin tosses), the first example (weather) describes a type of uncertainty often termed “ambiguity”, referring to uncertain outcomes with probabilities that are unknown due to imprecise beliefs about the state of the environment (also referred to as “estimation uncertainty”), whereas the second example (coin toss) illustrates another type of uncertainty often termed “risk”, referring to uncertain outcomes with known probabilities—a long-standing distinction in the decision-making literature (Knight 1921; Downloaded from https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhaa219/5894997 by Bibliothekssystem Universität Hamburg user on 26 August 2020